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针对溃疡性结肠炎中对英夫利昔单抗无应答者,我们首先和接下来应该做什么?

Focusing on non-responders to infliximab with ulcerative colitis, what can we do first and next?

机构信息

Department of Gastroenterology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou City, Gansu Province, China; Key Laboratory of Digestive Diseases, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou City, Gansu Province, China.

Department of Gastroenterology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou City, Gansu Province, China.

出版信息

Int Immunopharmacol. 2024 Nov 15;141:112943. doi: 10.1016/j.intimp.2024.112943. Epub 2024 Aug 24.

Abstract

BACKGROUND

Ulcerative colitis (UC) is a chronic immune-mediated inflammation of the colorectum, for which infliximab (IFX) is currently the mainstay of treatment. However, one-third of patients with UC still fail to benefit from the IFX therapy, and early exposure to IFX impairs the efficacy of other subsequent biologics. Therefore, personalized therapeutic system is urgently needed to assist in clinical decision-making and precision treatment.

METHODS

Four microarray datasets of colonic biopsies from UC patients treated with IFX were obtained from the GEO database to form the Training Cohort and Validation Cohort. Differentially expressed genes (DEGs) in Training Cohort were identified and enriched for GO, KEGG and immune cell infiltration analysis. A prediction model for IFX efficacy was developed based on the LASSO and Logistic regression. The predictive accuracy of the model was verified by the Validation Cohort, and the model-genes/proteins were validated by immunohistochemistry. Gene-drug, gene-ncRNA interaction analysis were performed to identify drugs or non-coding RNAs (ncRNAs) that potentially interacted with the model-genes. Homology Modeling and Molecular Docking were conducted to filter the optimal candidate as the subsequent adjuvant or alternative for IFX in predicted non-responders. At last, the down-regulation of the key model-gene/protein CYP24A1 by the drug candidate Deferasirox was verified by Western Blot and qRT-PCR Assay based on cellular experiments.

RESULTS

A total of 113 DEGs were identified in the Training Cohort, mainly enriched in inflammatory cell chemotaxis, migration, and response to molecules derived from intestinal microbiota. Activated pro-inflammatory innate immune cells, including neutrophils, M1 macrophages, activated dendritic cells and mast cells, were significantly enriched in colons of non-responders. The prediction model based on three model-genes (IFI44L, CYP24A1, and RGS1) exhibited strong predictive efficacy, with AUC values of 0.901 and 0.80 in the Training and Validation Cohorts, respectively. Higher expression of the three model-genes/proteins in colons of non-responders to IFX was confirmed by clinical colonic mucosal biopsies. 4 Drugs (Calcitriol, Lunacalcipol, Deferasirox, Telaprevir), 15 miRNAs and 66 corresponding lnRNAs interacting with model-genes were identified. The protein 3D structure of the key model-gene/protein (human-derived CYP24A1) was developed. Through the Molecular Docking and cellular experimental validation, Deferasirox, which significantly down-regulated both the RNA and protein expression of CYP24A1, was identified as the optimal adjuvant or alternative for IFX in predicted non-responders with UC.

CONCLUSION

This study developed a novel prediction model for pre-assessing the efficacy of IFX in patients with UC, as the first step towards personalized therapy. Meanwhile, drugs and non-coding RNAs were provided as potential candidates to develop the next-step precise treatment for the predicted non-responders. In particular, Defeasirox appears to hold promise as an adjuvant or alternative to IFX for the optimization of UC therapy.

摘要

背景

溃疡性结肠炎(UC)是一种慢性免疫介导的结肠炎症,目前英夫利昔单抗(IFX)是其主要的治疗方法。然而,仍有三分之一的 UC 患者无法从 IFX 治疗中获益,并且早期接触 IFX 会降低其他后续生物制剂的疗效。因此,迫切需要个性化的治疗系统来协助临床决策和精准治疗。

方法

从 GEO 数据库中获得了 4 个接受 IFX 治疗的 UC 患者结肠活检的微阵列数据集,形成了训练队列和验证队列。在训练队列中鉴定差异表达基因(DEGs),并进行 GO、KEGG 和免疫细胞浸润分析。基于 LASSO 和 Logistic 回归构建了 IFX 疗效预测模型。通过验证队列验证模型的预测准确性,并通过免疫组织化学验证模型基因/蛋白。进行基因-药物、基因-ncRNA 相互作用分析,以确定与模型基因潜在相互作用的药物或非编码 RNA(ncRNA)。进行同源建模和分子对接,以筛选出最佳候选药物作为预测无应答者中 IFX 的辅助药物或替代药物。最后,基于细胞实验,通过 Western Blot 和 qRT-PCR 验证候选药物地拉罗司对关键模型基因/蛋白 CYP24A1 的下调作用。

结果

在训练队列中鉴定出了 113 个 DEGs,主要富集在炎症细胞趋化、迁移和对来自肠道微生物群的分子的反应中。非应答者的结肠中明显富集了活化的促炎固有免疫细胞,包括中性粒细胞、M1 巨噬细胞、活化的树突状细胞和肥大细胞。基于三个模型基因(IFI44L、CYP24A1 和 RGS1)的预测模型具有很强的预测效能,在训练和验证队列中的 AUC 值分别为 0.901 和 0.80。通过临床结肠黏膜活检证实了 IFX 无应答者结肠中三个模型基因/蛋白的高表达。鉴定出了与模型基因相互作用的 4 种药物(骨化三醇、拉诺钙泊、地拉罗司、替拉瑞韦)、15 种 miRNA 和 66 种相应的 lnRNA。开发了关键模型基因/蛋白(人源 CYP24A1)的蛋白质 3D 结构。通过分子对接和细胞实验验证,确定地拉罗司是一种潜在的候选药物,它能显著下调 CYP24A1 的 RNA 和蛋白表达,可作为预测无应答者 UC 治疗的 IFX 的辅助药物或替代药物。

结论

本研究开发了一种新的预测模型,用于初步评估 UC 患者接受 IFX 治疗的疗效,这是迈向个性化治疗的第一步。同时,为开发预测无应答者的下一步精准治疗提供了药物和非编码 RNA 等潜在候选药物。特别是地拉罗司似乎有望成为优化 UC 治疗的 IFX 的辅助药物或替代药物。

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